Geotechnical design confronts uncertainties from incomplete subsurface knowledge, natural variability, geomaterial properties, construction errors, and differing solution models. Traditional approaches use conservative factors of safety or pre-calibrated partial factors to address uncertainties indirectly. Reliability-based design incorporates uncertainties directly but requires full statistical characterization, which is often unattainable in practice. Robust geotechnical design offers an alternative, by optimizing safety, cost, and robustness when uncertainties cannot be accurately quantified―where reliability-based and load and resistance factor design prove less effective. This first comprehensive book on robust geotechnical design presents detailed methodologies, design examples, and reviews existing methods, benefiting researchers and engineers interested in geotechnical and geological design under uncertainty.
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Wenping Gong is a Professor at China University of Geosciences in Wuhan. He received his PhD in civil engineering (geotechnical) from Clemson University, USA. His research focuses primarily on probabilistic site characterization, uncertainty analysis and design methods in geotechnical and geological engineering, and landslide risk recognition and assessment. He has published more than 100 papers in peer-reviewed international journals. Dr. Gong has already obtained several research projects from the Natural Science Foundation of China. He has received multiple awards, including the Richard Wolters Prize Runner-Up (IAEG), GEOSNet Young Researcher Award (GEOSNet), and Bright Spark lecture (ISSMGE). He is the Editor-in-Chief of Engineering Geology and also serves on the editorial boards of several journals, such as Bulletin of Engineering Geology and the Environment and Marine Georesources & Geotechnology.
C. Hsein Juang is an Emeritus Professor at Clemson University, USA, after 36 years of academic service (1982-2018). He was a visiting chair professor at many universities overseas, including National Central University, China, and Tongji University, China. Professor Juang earned his BS (1974) and MS (1976) degrees from National Cheng Kung University, Taiwan, and a PhD degree (1981) from Purdue University, USA. Dr. Juang has received many awards, including the GEOSNet Distinguished Award 2022, the Wilson Tang Lecturer 2019, the GEOSNet Award 2015, and the TK Hsieh Award 2001 by the Institution of Civil Engineers. Among his career achievements, Dr. Juang is most pleased to have been selected by his students as the Outstanding Teacher and to have graduated 22 doctoral students at Clemson University. Dr. Juang has served the geotechnical profession in various capacities, including as chair of the ASCE/GI RAM committee (2009-2012), conference chair for ASCE Georisk 2011, and Editor-in-Chief of Engineering Geology (2012-2024), among others. Dr. Juang has made many original contributions to soil liquefaction, supported excavation, reliability-based methods, and robust design.
Lei Wang is an Assistant Professor at University of Cincinnati, USA. He received his PhD degree from Clemson University, USA, in 2013. Dr. Wang has an extensive research experience in geotechnical engineering, including geotechnical risk and reliability, underground excavation and tunneling, soil/rock-structure interaction, numerical and centrifuge modeling, earth dams and levees, foundation engineering, and geotechnical earthquake engineering. He has published over 70 refereed journal papers. He was a recipient of many honors and awards, including the Best Paper Award by Taiwan Geotechnical Society. He serves on editorial board for internationa journals including Engineering Geology (Elsevier), Journal of Cold Regions Engineering (ASCE), Bulletin of Engineering Geology and the Environment (Springer), and Marine Georesources & Geotechnology (Taylor & Francis).
Chao Zhao is an Associate Professor at Yangtze University, China. He received his PhD in geological engineering from China University of Geosciences (Wuhan) in 2022. His main research interests include probabilistic site characterization and risk assessment of geohazards. He has published more than 20 papers in peer-reviewed international journals. He has already obtained several research projects from the Natural Science Foundation of China and the China Postdoctoral Science Foundation.
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Hardcover. Condition: new. Hardcover. Geotechnical design confronts uncertainties from incomplete subsurface knowledge, natural variability, geomaterial properties, construction errors, and differing solution models. Traditional approaches use conservative factors of safety or pre-calibrated partial factors to address uncertainties indirectly. Reliability-based design incorporates uncertainties directly but requires full statistical characterization, which is often unattainable in practice. Robust geotechnical design offers an alternative, by optimizing safety, cost, and robustness when uncertainties cannot be accurately quantifiedwhere reliability-based and load and resistance factor design prove less effective. This first comprehensive book on robust geotechnical design presents detailed methodologies, design examples, and reviews existing methods, benefiting researchers and engineers interested in geotechnical and geological design under uncertainty. Ground variability and limited information underpin uncertainties, so the best geotechnical design is probabilistic. This first book on robust geotechnical design presents detailed methodologies and design examples alongside other methods such as RBD, and LRFD for researchers and engineers. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032914244
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Hardcover. Condition: new. Hardcover. Geotechnical design confronts uncertainties from incomplete subsurface knowledge, natural variability, geomaterial properties, construction errors, and differing solution models. Traditional approaches use conservative factors of safety or pre-calibrated partial factors to address uncertainties indirectly. Reliability-based design incorporates uncertainties directly but requires full statistical characterization, which is often unattainable in practice. Robust geotechnical design offers an alternative, by optimizing safety, cost, and robustness when uncertainties cannot be accurately quantifiedwhere reliability-based and load and resistance factor design prove less effective. This first comprehensive book on robust geotechnical design presents detailed methodologies, design examples, and reviews existing methods, benefiting researchers and engineers interested in geotechnical and geological design under uncertainty. Ground variability and limited information underpin uncertainties, so the best geotechnical design is probabilistic. This first book on robust geotechnical design presents detailed methodologies and design examples alongside other methods such as RBD, and LRFD for researchers and engineers. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032914244
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Buch. Condition: Neu. Neuware - Geotechnical design confronts uncertainties from incomplete subsurface knowledge, natural variability, geomaterial properties, construction errors, and differing solution models. Traditional approaches use conservative factors of safety or pre-calibrated partial factors to address uncertainties indirectly. Reliability-based design incorporates uncertainties directly but requires full statistical characterization, which is often unattainable in practice. Robust geotechnical design offers an alternative, by optimizing safety, cost, and robustness when uncertainties cannot be accurately quantified-where reliability-based and load and resistance factor design prove less effective. This first comprehensive book on robust geotechnical design presents detailed methodologies, design examples, and reviews existing methods, benefiting researchers and engineers interested in geotechnical and geological design under uncertainty. Seller Inventory # 9781032914244